About: Simplilearn
Simplilearn is the world’s #1 online Bootcamp provider, enabling learners around the globe with rigorous and highly specialized training offered in partnership with world-renowned universities and leading corporations. We focus on emerging technologies and skills, such as data science, cloud computing, programming, and more — that are transforming the global economy. Our training is hands-on and immersive, including live virtual classes, integrated labs and projects, 24x7 support, and a collaborative learning environment. Over two million professionals and 2000 corporate training organizations across 150 countries have harnessed our award-winning programs to achieve their career and business goals.
Simplilearn has collaborated with Full stack Academy to leverage its widespread footprint in the US region and partnerships with Top US universities to grow internationally
Position Overview
The Part-Time Instructor for Artificial Intelligence and Machine Learning (AIML) plays a key role in delivering engaging and impactful learning experiences to adult learners enrolled in our online programs.
Instructors facilitate curriculum content, support student learning, and connect technical concepts to real-world industry applications. This role involves teaching live online sessions, mentoring students, providing feedback, and contributing to a collaborative instructional environment.
Classes are delivered 100% online in a synchronous format.
Job Summary
We are seeking experienced Agentic AI Trainers to deliver live online training sessions covering modern generative models, LLMs, LangChain, RAG, and prompt engineering with hands-on demos and projects.
Key Responsibilities
Deliver live, instructor-led online classes
Conduct hands-on demos, guided practices, and projects
Explain concepts using real-world use cases
Address learner queries and ensure engagement
Required Skills & Expertise
Generative AI & Foundation Models
Generative AI model types and applications
VAEs and GANs (architecture, use cases, limitations)
Transformer-based models and attention mechanisms
Self-attention and multi-head attention
Language Models & LLMs
Language models fundamentals and applications
Large Language Models (architecture, training, operations, types)
Retrieval-Augmented Generation (RAG)
RAG concepts, components, retrievers, and workflows
Real-world applications of RAG
LangChain
LangChain architecture and core components
Building applications using LangChain
Prompt, memory, chains, and model integration
Text generation pipelines with Hugging Face models
Prompt Engineering
Prompt fundamentals and optimization
Zero-shot, few-shot, CoT, Self-Consistency, ToT prompting
Prompt templates and LangChain prompts
Prompt engineering applications (data & synthetic data generation)
Model I/O & Data Handling
Model I/O (prompts, LLMs, output parsers)
Document loaders (CSV, PDF, HTML, JSON, Markdown)
Text splitters and embeddings in GenAI
Qualifications
8+ years of experience in Agentic Ai / Generative AI / NLP / LLMs
Strong proficiency in Python, LLM frameworks, and LangChain
Prior online or classroom training experience